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Xinjiang Brown cattle are a unique and widely distributed breed of dual-purpose cattle in the Xinjiang area of China, whose milk production performance differs from Holstein cattle. It has been known that variations in bacterial species of the gastrointestinal tract influence milk protein, fat, and lactose synthesis. However, the microbiota differences between Xinjiang Brown and Holstein cattle are less known. This study aims to compare the bacterial community composition of the rumen and feces of these two cattle breeds under the same dietary and management conditions. The 16s rRNA sequencing data and milk production of 18 Xinjiang Brown cows and 20 Holstein cows on the same farm were obtained for analysis. The results confirmed differences in milk production between Xinjiang Brown and Holstein cattle. Microbiota with different relative abundance between these two cattle breeds were identified, and their biological functions might be related to milk synthesis. This study increases the understanding of the differences in microbiota between Xinjiang Brown and Holstein cattle and might provide helpful information for microbiota composition optimization of these dairy cattle.
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BACKGROUND: Artificial neural networks (ANNs) have been extensively used in the field of medicine. The present hypothesis-free study sought to use an ANN to identify the characteristic genes of cervical cancer (CC). METHODS: RNA sequencing profiles were obtained from the GSE7410, GSE9750, GSE63514, and GSE52903 datasets. The differentially expressed genes (DEGs) were identified and compared between the normal and CC tissues. An ANN analysis was conducted to obtain the random-forest tree and to examine differences in gene filtering. A neural network model was established using the characteristic genes of CC, while the verification accuracy of the model was examined by Cox regression. The differences in the immune infiltrating cells between the normal cervical and CC tissues were compared by CIBERSORT (an analytical tool can provide an estimation of the abundances of member cell types in a mixed cell population). RESULTS: Nine genes' characteristics for CC were identified: cyclin-dependent kinase inhibitor 2A (CDKN2A), chromosome 1 open reading frame 112 (C1orf112), helicase, lymphoid-specific (HELLS), mini-chromosome maintenance protein 5 (MCM5), mini-chromosome maintenance protein 2 (MCM2), kinetochore associated 1 (KNTC1), cysteine-rich secretory protein 3 (CRISP3), phytanoyl-CoA 2-hydroxylase interacting protein (PHYHIP), and cornulin (CRNN). CONCLUSIONS: ANN is a robust neural network model that can be used to potentially predict CC based on the gene score. It can provide novel insights into the pathogenesis and molecular mechanisms of CC.
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Neoplasias del Cuello Uterino , Femenino , Humanos , Neoplasias del Cuello Uterino/genética , Neoplasias del Cuello Uterino/patología , Biología Computacional , Redes Neurales de la ComputaciónRESUMEN
The aging of microplastics (MPs) is extremely influenced by photochemically-produced reactive intermediates (PPRIs), which are mediated by natural photosensitive substances. Algal extracellular polymeric substances (EPS) can produce PPRIs when exposed to sunlight. Nonetheless, the specific role of EPS in the aging process of MPs remains unclear. This work systematically explored the aging process of polystyrene (PS) MPs in the EPS secreted by Chlorella vulgaris under simulated sunlight irradiation. The results revealed that the existence of EPS accelerated the degradation of PS MPs into particles with sizes less than 1 µm, while also facilitating the formation of hydroxy groups on the surface. The release rate of dissolved organic matter (DOM) from PS MPs was elevated from 0.120 mg·L-1·day-1 to 0.577 mg·L-1·day-1. The primary factor contributing to the elevated levels of DOM was humic acid-like compounds generated through the breakdown of PS. EPS accelerated the aging process of PS MPs by primarily mediating the formation of triplet excited states (3EPS*), singlet oxygen (1O2), and superoxide radicals (O2â-), resulting in indirect degradation. 3EPS* was found to have the most substantial impact. This study makes a significant contribution to advance understanding of the environmental fate of MPs in aquatic environments impacted by algal blooms.
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Chlorella vulgaris , Contaminantes Químicos del Agua , Microplásticos , Plásticos , Matriz Extracelular de Sustancias Poliméricas/química , Luz Solar , Poliestirenos , Contaminantes Químicos del Agua/análisis , Sustancias Húmicas/análisisRESUMEN
BACKGROUND: Demodex blepharitis (DB) is a common disease of the ocular surface. The characteristics of the bacterial community in eyelash roots after Demodex infestation are still unknown. Knowledge of the characteristics of the bacterial community of eyelash follicles in patients with DB can provide valuable insights for guiding the diagnosis and treatment of DB. METHODS: Twenty-five patients with DB (DB group) and 21 non-DB volunteers (control group) were enrolled in the study. Eyelashes from the upper eyelid of the right eye were sampled, and 16S ribosomal DNA (rDNA) sequencing was performed to determine the V3-V4 regions of the microbial 16S rDNA gene within 1 month of infestation. The sequencing data of the two groups were analyzed and compared. The effect of the bacterium Burkholderia on the survival of Demodex mites was evaluated using Demodex obtained from 12 patients with DB other that the patients in the DB group. RESULTS: A total of 31 phyla and 862 genera were identified in the DB and control groups. The five most abundant phyla in the two groups were Proteobacteria, Firmicutes, Actinobacteria, Bacteroidetes and Cyanobacteria. The abundance of Actinomycetes was significantly higher in the DB group than in the control group. At the genus level, the five most abundant genera in the two groups were Pseudomonas, Burkholderia-Caballeronia-Paraburkholderia, Rolstonia and Acinetobacter; Clostridium sensu stricto 1 was abundant in the control group and Corynebacterium_1 was abundant in the DB group. Compared with the control group, the abundance of Burkholderia-Caballeronia-Paraburkholderia was 2.36-fold lower in the DB group. Linear discriminant analysis Effect Size (LEfSe) analysis revealed Burkholderia-Caballeronia-Paraburkholderia, SC_I_84_unclassified, Nonmyxobacteria and Succinvibrio to be the major biomarkers in the control group and Catenibacterium and Lachnospiraceae NK4A136 group to be the major biomarkers in the DB group. To explore the performance of these optimal marker models, receiver operational characteristic curve analysis was performed, and the average area under the curve value of Burkholderia-Caballeronia-Paraburkholderia was 0.7448. Burkholderia cepacia isolated from normal human eyelashes was fermented, and the Demodex mites isolated from patient eyelashes were cultured together with its fermented supernatant. The results showed that the fermentation supernatant could significantly reduce the survival time of the Demodex mites, suggesting the potential therapeutic value of this bacterium against Demodex. CONCLUSIONS: The composition of the bacterial community in the eyelashes of DB patients differed from that in eyelashes of healthy volunteers, revealing a decrease in bacterial diversity in infested eyelashes. This decrease may be related to the occurrence and development of DB. The supernatant of Burkholderia cepacia culture medium was found to inhibit the growth of Demodex in eyelash hair follicles, providing a new insight with potential applications for the clinical treatment of Demodex infestation.